The price of cider: empirical analysis in Québec province
Bibliographic record
Abstract
Purpose The purpose of this paper is to investigate the main factors and mechanisms that govern the price of cider, and to apply the analysis to the price of ciders in the Province of Québec, Canada. Design/methodology/approach The analysis is following the methodology applied to the determinants of the price of wine. A model for the price of cider is estimated with 70 prices representing five regions and five types of products. Findings The analysis is limited to one geographical factor, i.e. the region of origin and factors related to the producer, i.e. the age and the size of the firm. The results conclude on the importance of geographical factors related to the region of origin. The relationship between the price of ciders and the region of origin is statistically significant at the 1 percent level for two regions and shows a high premium for ciders produced in these two regions. Production factors related to the age and the size of the production unit although showing the expected sign are not statistically significant to conclude on the impact. There is a small premium for producing effervescent cider compared to still or rosé cider but the most statistically significant results at a 1 percent level are for ice ciders and fortified ciders which are two typical products from Québec. Research limitations/implications The analysis has important potential implications on the role of certification of origin. Cider regions in Québec, Canada have recently defined quality standards applied to specialties like Ice cider and Fire ciders. The choice of high quality products is reflected in the premium associated to the price of these products. Originality/value Contrary to the wine sector, there is a lack of research and literature on the determinants of the price of ciders. This study is the first to propose a pricing model to examine some of the determinants of prices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".